Obesity and Health-Related Decisions: An Empirical Model of The Determinants of Weight Status

Leonardo Fabio Morales, P. Gordon-Larsen, David K. Guilkey
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引用次数: 11

Abstract

Using Add Health, a very comprehensive longitudinal data set of teenagers and young adults in the United States, we estimate a structural dynamic model of the determinants of obesity. In addition to including many of the well-recognized endogenous factors mentioned in the literature as obesity determinants, i.e., physical activity, smoking, a proxy for food consumption, and childbearing, we also model the residential location as a choice variable, relevant to the young-to middle-aged adult, as a major component. This allows us to control for an individual’s self-selection into communities which possess the types of amenities in the built environment which in turn affect their behaviors such as physical activity and fast food consumption. We specify reduced form equations for all these endogenous demand decisions, together with an obesity structural equation. The whole system of equations is jointly estimated by a semi-parametric full information log-likelihood method that allows for a general pattern of correlation in the errors across equations. Simulations are then used to allow us to quantify the effects of these endogenous factors on the probability of obesity. A key finding is that controlling for residential self-selection has important substantive implications. To our knowledge, this has not been yet documented within a full information maximum likelihood framework.
肥胖与健康相关决策:体重状况决定因素的实证模型
使用Add Health,一个非常全面的美国青少年和年轻人的纵向数据集,我们估计了肥胖决定因素的结构动态模型。除了包括文献中提到的许多公认的内源性因素作为肥胖决定因素,即体育活动,吸烟,食物消费的代理和生育,我们还将居住地点作为一个选择变量建模,与青年到中年人相关,作为一个主要组成部分。这使我们能够控制个人对社区的自我选择,这些社区拥有建筑环境中的便利设施类型,从而影响他们的行为,如体育活动和快餐消费。我们指定了所有这些内生需求决策的简化形式方程,以及肥胖结构方程。整个方程组通过半参数全信息对数似然方法进行联合估计,该方法允许跨方程误差的一般相关模式。然后,模拟可以让我们量化这些内源性因素对肥胖概率的影响。一个重要的发现是,控制居住自我选择具有重要的实质性意义。据我们所知,这还没有在一个完整的信息最大可能性框架内被记录下来。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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